class_docstr: This is the base class for a probability distributions,
  over which we take the expectations in the expectations framework.
class_docstr_tok: ["This","is","the","base","class","for","a","probability","distributions",",","over","which","we","take","the","expectations","in","the","expectations","framework","."]
docstr: Return the shape of this distribution.
  
  Shape should be some variation of ``[N, D]``, where:
  
  * ``N`` is the number of data points.
  * ``D`` is the number of input dimensions.
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code: def shape(self) -> Shape:
      """
      Return the shape of this distribution.
  
      Shape should be some variation of ``[N, D]``, where:
  
      * ``N`` is the number of data points.
      * ``D`` is the number of input dimensions.
      """
  
file_path: GPflow/gpflow/probability_distributions.py
imports: from abc import ABC, abstractmethod
  from check_shapes import ErrorContext, Shape, check_shapes, register_get_shape
  from .base import TensorType
label_desc: Use image node_id 1 for calling the ProbabilityDistribution obj's underlying member method code with example usage: obj.shape() without return types